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Article

Interpretation of Hot Spots in Wuhan New Town Development and Analysis of Influencing Factors Based on Spatio-Temporal Pattern Mining

by
Haijuan Zhao
1,2,
Yan Long
3,
Nina Wang
4,
Shiqi Luo
1,
Xi Liu
1,
Tianyue Luo
5,
Guoen Wang
1 and
Xuejun Liu
1,6,*
1
School of Urban Design, Wuhan University, Wuhan 430072, China
2
Wuhan Design Consultation Group Co., Ltd., Wuhan 430023, China
3
School of Art and Design, Wuhan University of Science and Technology, Wuhan 430065, China
4
School of Applied Information Systems, Cornell University, 2 West Loop Road, New York, NY 10044, USA
5
Wuhan Planning & Design Institute (Wuhan Transportation Development Strategy Institute), Wuhan 430010, China
6
Research Center for Digital City, Wuhan University, Wuhan 430072, China
*
Author to whom correspondence should be addressed.
ISPRS Int. J. Geo-Inf. 2024, 13(6), 186; https://doi.org/10.3390/ijgi13060186
Submission received: 1 April 2024 / Revised: 23 May 2024 / Accepted: 27 May 2024 / Published: 3 June 2024
(This article belongs to the Special Issue Application of Geographical Information System in Urban Design, Management or Evaluation)
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Abstract

The construction of new towns is one of the main measures to evacuate urban populations and promote regional coordination and urban–rural integration in China. Mining the spatio-temporal pattern of new town hot spots based on multivariate data and analyzing the influencing factors of new town construction hot spots can provide a strategic basis for new town construction, but few researchers have extracted and analyzed the influencing factors of new town internal hot spots and their classification. In order to define the key points of Wuhan’s new town construction and promote the construction of new cities in an orderly and efficient manner, this paper first constructs a space-time cube based on the luminous remote sensing data from 2010 to 2019, extracts hot spots and emerging hot spots in Wuhan New City, selects 14 influencing factor indicators such as population density, and uses bivariate Moran’s index to analyze the influencing factors of hot spots, indicating that the number of bus stops and vegetation coverage rate are the most significant. Secondly, the disorderly multivariate logistic regression model is used to analyze the influencing factors of emerging hot spots. The results show that population density, vegetation coverage, road density, distance to water bodies, and distance to train stations are the most significant factors. Finally, based on the analysis results, some relevant suggestions for the construction of Wuhan New City are proposed, providing theoretical support for the planning and policy guidance of new cities, and offering reference for the construction of new towns in other cities, promoting the construction of high-quality cities.
Keywords: urban hot spots; spatio-temporal pattern mining; space-time cube; bivariate Moran’s index; disorderly multivariate logistic regression model urban hot spots; spatio-temporal pattern mining; space-time cube; bivariate Moran’s index; disorderly multivariate logistic regression model

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MDPI and ACS Style

Zhao, H.; Long, Y.; Wang, N.; Luo, S.; Liu, X.; Luo, T.; Wang, G.; Liu, X. Interpretation of Hot Spots in Wuhan New Town Development and Analysis of Influencing Factors Based on Spatio-Temporal Pattern Mining. ISPRS Int. J. Geo-Inf. 2024, 13, 186. https://doi.org/10.3390/ijgi13060186

AMA Style

Zhao H, Long Y, Wang N, Luo S, Liu X, Luo T, Wang G, Liu X. Interpretation of Hot Spots in Wuhan New Town Development and Analysis of Influencing Factors Based on Spatio-Temporal Pattern Mining. ISPRS International Journal of Geo-Information. 2024; 13(6):186. https://doi.org/10.3390/ijgi13060186

Chicago/Turabian Style

Zhao, Haijuan, Yan Long, Nina Wang, Shiqi Luo, Xi Liu, Tianyue Luo, Guoen Wang, and Xuejun Liu. 2024. "Interpretation of Hot Spots in Wuhan New Town Development and Analysis of Influencing Factors Based on Spatio-Temporal Pattern Mining" ISPRS International Journal of Geo-Information 13, no. 6: 186. https://doi.org/10.3390/ijgi13060186

APA Style

Zhao, H., Long, Y., Wang, N., Luo, S., Liu, X., Luo, T., Wang, G., & Liu, X. (2024). Interpretation of Hot Spots in Wuhan New Town Development and Analysis of Influencing Factors Based on Spatio-Temporal Pattern Mining. ISPRS International Journal of Geo-Information, 13(6), 186. https://doi.org/10.3390/ijgi13060186

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